Authors:
Djamel Merad
1
;
Stephanie Metz
2
and
Serge Miguet
3
Affiliations:
1
LIRIS laboratory, France
;
2
ICAR Laboratory, France
;
3
LIRIS Laboratory, France
Keyword(s):
Head tracking, Pattern recognition, Machine vision.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Robotics and Automation
;
Virtual Environment, Virtual and Augmented Reality
;
Vision, Recognition and Reconstruction
Abstract:
Our work focuses on the interdisciplinary field of detailed analysis of behaviors exhibited by individuals during sessions of distributed collaboration. With a particular focus on ergonomics, we propose new mechanisms to be integrated into existing tools to enable increased productivity in distributed learning and working. Our technique is to record ocular movements (eye tracking) to analyze various scenarios of distributed collaboration in the context of computer-based training. In this article, we present a low-cost oculometric device that is capable of making ocular measurements without interfering with the natural behavior of the subject. We expect that this device could be employed anywhere that a natural, non-intrusive method of observation is required, and its low-cost permits it to be readily integrated into existing popular tools, particularly E-learning campus.